A method for quantifying the degree of fusion between new and old asphalt

Abstract

The present invention discloses a quantification method for the fusion degree of new and old asphalt, which relates to the technical field of road hot recycling. In the present invention, the asphalt film samples on the surface of the RAP material are extracted layer by layer, combined with the potassium bromide thin film technology to form a uniform film, and then the Fourier transform infrared spectroscopy (FTIR) technology is used to obtain the spectral characteristic data and characteristic peaks of each layer of samples. And methods such as baseline correction and standardization are used to normalize the data, and then the first derivative is used to extract the characteristic peak positions and intensities to construct a standard curve; and the dynamic time warping (DTW) algorithm is used to quantify the matching degree of the spectral curves of new and old asphalt, and a fusion similarity index (FSI) is defined to effectively quantify the similarity of the chemical composition distribution of new and old asphalt; at the same time, the microscopic infrared spectroscopy technology is used to further perform local scanning on the spectral distribution on the surface of the RAP particles, and a fusion heat map is generated in combination with the FSI results to visually display the local fusion differences between new and old asphalt.

Description

Technical Field

[0001] The invention relates to the technical field of road thermal regeneration, in particular to a method for quantifying the degree of fusion of new and old asphalt. Background Art

[0002] In road thermal regeneration technology, the degree of fusion between new and old asphalt is a key factor affecting the performance of recycled asphalt mixture. In order to quantitatively evaluate the fusion effect, existing studies have used infrared spectroscopy characteristic peak ratio analysis, mechanical properties testing and other methods to provide fusion degree data under laboratory conditions. However, most of these methods are based on the assumption of material mixing uniformity and characterize the fusion effect of new and old asphalt by extracting the average characteristics of the overall or surface asphalt.

[0003] However, in actual projects, the old asphalt and new asphalt in RAP (recycled asphalt mixture) are often not completely evenly distributed. Due to the uneven particle size distribution of the recycled material, insufficient mixing or local changes in heating conditions during the construction process, the spatial fusion performance of the new and old asphalt may not be consistent. Traditional methods are often based on overall evaluation and lack an effective description of local fusion problems, which leads to limitations in the quantitative results of the degree of fusion and makes it difficult to quantify the impact of uneven material distribution on the performance of the mixture.

[0004] To address this problem, some traditional methods adjust the mixing time, increase the mixing temperature, or add enhancers to the regeneration agent to improve the overall fusion ability for RAP materials of different particle sizes; however, such improvements are still difficult to fundamentally solve the quantitative problem of insufficient fusion in local areas, limiting the guidance of the technology for actual engineering. Therefore, a quantitative method for the fusion degree of new and old asphalt is urgently needed to solve such problems. Summary of the invention

[0005] In view of the above existing problems, the present invention is proposed.

[0006] The present invention provides a method for quantifying the degree of fusion of new and old asphalt to solve the problem that the existing method only provides certain performance indicators when quantifying the degree of fusion of new and old asphalt, but the quantification effect is poor when facing the fusion differences in local areas.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] The embodiment of the present invention provides a method for quantifying the degree of fusion of new and old asphalt, which comprises:

[0009] Step S1, using a selective solvent to extract the asphalt film on the surface of the RAP material in layers, obtaining asphalt film samples at different layers, dissolving the extracted asphalt film samples at each layer and forming a uniform film by potassium bromide flake technology;

[0010] Step S2, using a Fourier transform infrared (FTIR) spectrometer to perform spectral analysis on the thin film samples of each layer formed in step S1, to obtain spectral characteristic data and characteristic peaks, to pre-process the spectral characteristic data, including baseline correction and standardization, and to convert the characteristic peaks and spectral characteristic data into a standardized curve;

[0011] Step S3, inputting the standardized curves of each layer of asphalt film obtained in step S2 into the dynamic time warping DTW algorithm, calculating the minimum warping distance between the new and old asphalt, defining the fusion similarity index FSI based on this distance, quantitatively describing the similarity of the new and old asphalt in chemical composition distribution, and forming a preliminary fusion analysis of each layer of asphalt film;

[0012] Step S4, based on the layered extraction samples in step S1, the spectral distribution of each layer of asphalt film on the surface of RAP material particles is scanned by using micro-infrared spectroscopy technology to capture the changes in spectral characteristics of local areas; combined with the FSI results calculated in step S3, the spatial distribution of the particle surface is regionalized and analyzed to generate a fusion heat map;

[0013] Step S5, combining the FSI result calculated in step S3 with the fusion heat map generated in step S4, analyzing the overall fusion uniformity characteristics of the new and old asphalt, and constructing a UFM model for evaluating the overall fusion uniformity; the UFM model quantifies the fusion depth and uniformity of the new and old asphalt by integrating local fusion characteristics and spectral similarity data, and generates intuitive visualization results, providing data support and theoretical basis for optimizing the regeneration process and construction parameters.

[0014] As a preferred embodiment of the method for quantifying the degree of fusion of new and old asphalt described in the present invention, in step S1, sample preparation and layered extraction are performed, and the sample preparation step includes:

[0015] Place the RAP material on a sieve to remove large particles and debris, rinse with anhydrous ethanol or deionized water to remove surface dust and impurities, and then dry.

[0016] According to the polarity of the asphalt component of the target extraction layer, a solvent system with different polarity gradients is selected for dissolution, and the solvent polarity ratio is adjusted according to the stratification target. The solvent ratio adjusted according to the stratification target is set as follows:

[0017] First extraction: Use low polarity solvent to dissolve non-polar components.

[0018] Second extraction: Use medium polarity solvent to extract the gum.

[0019] The third extraction layer: using a highly polar solvent to dissolve the asphaltenes;

[0020] The steps of the layered extraction are:

[0021] The RAP material is placed in a beaker, and a low-polarity solvent is added to mix with the RAP and stirred to obtain a mixture; the mixture is then centrifuged in a centrifuge to separate the dissolved asphalt solution and the undissolved residual particles, and the undissolved particles are repeatedly extracted with a fresh first solvent to completely extract the target component; the residual particles are then transferred to a new beaker, and medium-polarity and high-polarity solvents are added in sequence, and the soaking and centrifugation steps are repeated to obtain asphalt solutions of different levels;

[0022] The asphalt solution extracted from each layer was evaporated by a rotary evaporator to remove excess solvent, thus obtaining asphalt samples of different layers;

[0023] Dissolve each layer of asphalt samples obtained by extraction in carbon tetrachloride or dichloromethane, stir thoroughly, drop the solution on the potassium bromide window slice, spread it evenly with a glass rod to evenly cover the solution; then place the slice in a drying oven and let it stand to dry to form a uniform film.

[0024] As a preferred solution of the method for quantifying the degree of fusion of new and old asphalt described in the present invention, the steps of obtaining spectral characteristic data and characteristic peaks and preprocessing the spectral characteristic data are as follows:

[0025] Scan the sample with an FTIR spectrometer and record the absorption spectrum over a range of wavenumbers , defined as:

[0026] ,

[0027] in, The wave number is The absorbance at The wave number is The background light intensity at The wave number is The sample transmission light intensity at

[0028] The spectral data was baseline corrected to remove the background signal. The correction formula is:

[0029] ,

[0030] in, The wave number is The corrected absorbance is The wave number is The fitted baseline function at

[0031] The corrected spectrum is standardized to eliminate the amplitude difference. The standardization formula is:

[0032] ,

[0033] in, The wave number is The standardized absorbance at and represent the minimum and maximum values ​​of the corrected spectrum, respectively.

[0034] As a preferred embodiment of the method for quantifying the degree of fusion of new and old asphalt described in the present invention, the step of converting the characteristic peak value and spectral characteristic data into a standardized curve is as follows:

[0035] Characteristic peak extraction is performed, and the characteristic peak position and intensity are identified by the first-order derivative. The identification formula is:

[0036] ,

[0037] ,

[0038] in, Indicates The characteristic peak wave number, Wave number The normalized absorbance intensity at

[0039] A standardized curve is constructed based on the extracted characteristic peaks. The curve formula is:

[0040] ,

[0041] in, Indicates Normalized curve of the thin film sample, is the total number of characteristic peaks, and Respectively Layer of thin film The wave number and intensity of the characteristic peaks, is the Dirac function, label the wave number location.

[0042] As a preferred solution of the method for quantifying the degree of fusion of new and old asphalt described in the present invention, the steps of calculating the minimum regular distance between the new and old asphalt and defining the fusion similarity index FSI based on the distance are as follows:

[0043] Input the normalization curve, set The standardized curves of the new and old asphalt samples are and , define the matching path of the two curves , so that the total path distance is minimized, the path calculation formula is:

[0044] ,

[0045] in, is the total number of path points, and The first The wave number position of the point in the new and old curves,

[0046] Calculate the total distance of the matching path using the following formula:

[0047] ,

[0048] in, For the The minimum regular distance between the new and old asphalt layers, For path The weight of the point, represents the Euclidean distance, defined as .

[0049] As a preferred solution of the method for quantifying the degree of fusion of new and old asphalt described in the present invention, the step of calculating the minimum regular distance between the new and old asphalt and defining the fusion similarity index FSI based on the distance also includes:

[0050] Fusion similarity definition, based on Definition Layer fusion similarity index , the fusion formula is:

[0051] ,

[0052] in, is the distance adjustment factor,

[0053] The overall fusion similarity of new and old asphalt is calculated by weighted average, and the weighted formula is:

[0054] ,

[0055] in, is the total number of layers, For the The weight of the layer.

[0056] As a preferred embodiment of the method for quantifying the degree of fusion of new and old asphalt described in the present invention, the step of regionalizing the spatial distribution of the particle surface is as follows:

[0057] Perform grid scanning to divide the surface of RAP particles into The two-dimensional grid of each grid point is ,in , Indicates the row and column positions of the grid,

[0058] At each grid point Collect spectra , and extract characteristic peaks and the corresponding absorbance intensity , the extracted content is expressed as:

[0059] ,

[0060] in, Represents a grid point The spectral signal, is the grid point The number of characteristic peaks on is the Dirac function, used to mark the wave number location.

[0061] As a preferred solution of the method for quantifying the degree of fusion of new and old asphalt described in the present invention, the step of generating the fusion heat map is:

[0062] Perform regional characteristic calculations, combined with the calculations in step S3 , calculate the regional characteristic value for the grid point , the calculation formula is:

[0063] ,

[0064] in, Represents a grid point The regional characteristic value of is the total number of layers, For the The fusion similarity of the layers, is a two-dimensional Gaussian kernel function used to weight the influence of neighboring points.

[0065] Generate fusion heat map after normalization :

[0066] ,

[0067] in, is the normalized heat map value, and They are The minimum and maximum values ​​of .

[0068] As a preferred solution of the method for quantifying the degree of fusion of new and old asphalt described in the present invention, the step of constructing the UFM model for evaluating the overall fusion uniformity is as follows:

[0069] Calculate the local uniformity and define the local uniformity index as :

[0070] ,

[0071] in, is the grid point The local uniformity value of For heatmap at point The gradient amplitude indicates the degree of local change.

[0072] Calculate global uniformity based on local uniformity Calculate the global uniformity average , the calculation formula is:

[0073] ,

[0074] in, represents the average uniformity of all grid points, and is the number of grid divisions,

[0075] Calculating local uniformity Standard Deviation , the calculation formula is:

[0076] ,

[0077] in, Indicates the degree of uniformity fluctuation.

[0078] As a preferred solution of the method for quantifying the degree of fusion of new and old asphalt described in the present invention, the step of constructing the UFM model for evaluating the overall fusion uniformity also includes:

[0079] Constructing UFM model based on uniformity average and standard deviation Constructing an overall fusion uniformity evaluation model , the model is expressed as:

[0080] ,

[0081] in, Represents the overall fusion uniformity index,

[0082] Perform regional fluctuation analysis and calculate uniformity fluctuation index based on local second-order gradient of heat map , the calculation formula is:

[0083] ,

[0084] in, represents the intensity of spatial fluctuations in the heat map, It is the Laplacian operator of the heat map, which measures the severity of local changes.

[0085] The beneficial effects of the present invention are as follows: In the present invention, the asphalt film samples on the surface of the RAP material are extracted in layers, and a uniform film is formed by combining the potassium bromide thin film technology, and then the spectral characteristic data and characteristic peaks of each layer of samples are obtained by Fourier transform infrared spectroscopy FTIR technology, and the data are normalized by baseline correction and standardization methods, and then the characteristic peak position and intensity are extracted by first-order derivative, and a standardized curve is constructed to eliminate background interference and differences between samples; the dynamic time warping DTW algorithm is used to quantify the degree of matching of the spectral curves of the new and old asphalts, and the fusion similarity index FSI is defined to effectively quantify the similarity of the new and old asphalts in the distribution of chemical components, and an evaluation of the overall fusion effect is provided by the weighted stratification method; at the same time, the microscopic infrared spectroscopy technology is used to further perform a local scan of the spectral distribution of the RAP particle surface, and a fusion heat map is generated in combination with the FSI results to intuitively display the local fusion differences between the new and old asphalts, solving the problem that it is difficult to capture regional characteristics in traditional methods.

[0086] The present invention combines the fusion thermal map data to construct an overall fusion uniformity evaluation model UFM. By defining local uniformity, global uniformity and spatial fluctuation intensity, the fusion depth and uniformity of new and old asphalt are comprehensively quantified. This not only improves the scientific nature of the quantification method, but also conducts a systematic evaluation from the local to the overall, providing reliable data support for optimizing the regeneration process and construction parameters. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0088] Figure 1 The present invention is a flow chart of the method for quantifying the degree of fusion between new and old asphalt. DETAILED DESCRIPTION

[0089] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0090] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0091] Second, the "one embodiment" or "embodiment" referred to herein means a specific feature, structure or characteristic that may be included in at least one implementation manner of the present invention. The "in one embodiment" that appears in different places in this specification does not all refer to the same embodiment, nor is it an embodiment that is separate or selectively mutually exclusive with other embodiments.

[0092] Embodiment 1, referring to Figure 1 , this embodiment provides a method for quantifying the fusion degree of new and old asphalt, including the following steps:

[0093] Step S1, perform fractional extraction on the asphalt film on the surface of the RAP material using a selective solvent to obtain asphalt film samples at different levels, dissolve the asphalt film samples extracted from each layer and form a uniform film through the potassium bromide thin film technique;

[0094] In step S1, sample preparation and fractional extraction are carried out. The sample preparation steps include:

[0095] Place the RAP material in a sieve, screen out large particles and debris, rinse with absolute ethanol or deionized water to remove surface dust and impurities, and then dry.

[0096] Select a solvent system with different polarity gradients to dissolve according to the polarity of the asphalt components in the target extraction layer, and adjust the solvent polarity ratio according to the layering target. Let the solvent ratio adjusted according to the layering target be:

[0097] First layer extraction: Use a low-polarity solvent to dissolve non-polar components.

[0098] Second layer extraction: Use a medium-polarity solvent to extract resins.

[0099] Third layer extraction: Use a high-polarity solvent to dissolve asphaltenes;

[0100] The steps of fractional extraction are:

[0101] Place the RAP material in a beaker, add a low-polarity solvent and mix and stir with the RAP to obtain a mixture; then place the mixture in a centrifuge to centrifugally separate the dissolved asphalt solution and undissolved residual particles, repeat the extraction of the undissolved particles with fresh first solvent until the target components are completely extracted; then transfer the residual particles to a new beaker, successively add medium-polarity and high-polarity solvents, and repeat the soaking and centrifugation steps to obtain asphalt solutions at different levels;

[0102] Evaporate the excess solvent from the asphalt solution obtained by each layer of extraction through a rotary evaporator to obtain asphalt samples at different levels;

[0103] Dissolve each layer of the extracted asphalt sample in carbon tetrachloride or dichloromethane, stir well, drop the solution onto a potassium bromide window thin slice, spread it evenly with a glass rod, and uniformly cover the solution; then place the thin slice in an oven and let it stand and dry to form a uniform film;

[0104] Step S2: Use a Fourier transform infrared (FTIR) spectrometer to perform spectral analysis on each layer of the thin film sample formed in Step S1, obtain spectral characteristic data and characteristic peak values, preprocess the spectral characteristic data, including baseline correction and normalization, and convert the characteristic peak values and spectral characteristic data into a normalized curve;

[0105] The steps of obtaining spectral characteristic data and characteristic peak values and preprocessing the spectral characteristic data are as follows:

[0106] Scan the sample with an FTIR spectrometer and record the absorption spectrum within the wavenumber range , defined as:

[0107] ,

[0108] where represents the absorbance at a wavenumber of , is the background light intensity at a wavenumber of , is the transmitted light intensity of the sample at a wavenumber of .

[0109] Perform baseline correction on the spectral data to remove the background signal. The correction formula is:

[0110] ,

[0111] where is the corrected absorbance at a wavenumber of , is the fitted baseline function at a wavenumber of .

[0112] Normalize the corrected spectrum to eliminate the amplitude difference. The normalization formula is:

[0113] ,

[0114] where is the normalized absorbance at a wavenumber of , and represent the minimum and maximum values of the corrected spectrum, respectively;

[0115] The steps of converting the characteristic peak values and spectral characteristic data into a normalized curve are as follows:

[0116] Perform characteristic peak extraction, identify the positions and intensities of characteristic peaks through the first derivative, and the identification formula is:

[0117] ,

[0118] ,

[0119] wherein, represents the wave number of the th characteristic peak, is the normalized absorbance intensity at the wave number .

[0120] Construct a normalized curve based on the extracted characteristic peaks, and the curve formula is:

[0121] ,

[0122] wherein, represents the normalized curve of the rd layer of thin film sample, is the total number of characteristic peaks, and are respectively the wave number and intensity of the th characteristic peak of the rd layer of thin film, is the Dirac function, marking the position of the wave number .

[0123] Specifically, through spectral acquisition, baseline correction, normalization processing, and characteristic peak extraction, the spectral data is converted into a normalized curve, effectively eliminating background interference and differences between samples, and reflecting the chemical characteristics of each layer of asphalt film samples.

[0124] Step S3: Input the normalized curves of each layer of asphalt film obtained in Step S2 into the dynamic time warping (DTW) algorithm, calculate the minimum warping distance between the new and old asphalt, define a fusion similarity index (FSI) based on this distance, quantitatively describe the similarity in the chemical composition distribution between the new and old asphalt, and form a preliminary fusion analysis of each layer of asphalt film;

[0125] The steps of calculating the minimum warping distance between the new and old asphalt and defining the fusion similarity index (FSI) based on this distance are as follows:

[0126] Input the normalized curves. Let the normalized curves of the new and old asphalt samples of the th layer be and respectively, define the matching path of the two curves to minimize the total distance of the path, and the path calculation formula is:

[0127] ,

[0128] Among them, is the total number of path points, and are respectively the wavenumber positions of the -th point in the old and new curves of the path,

[0129] Calculate the total distance of the matching path. The calculation formula is:

[0130] ,

[0131] Among them, is the minimum regularization distance between the old and new asphalt of the -th layer, is the weight of the -th point of the path, represents the Euclidean distance, defined as .

[0132] Calculate the minimum regularization distance between the old and new asphalt. The steps to define the fusion similarity index FSI based on this distance also include,

[0133] Definition of fusion similarity. Based on Define the fusion similarity index of the -th layer. The fusion formula is:

[0134] ,

[0135] Among them, is the distance adjustment factor,

[0136] Calculate the overall fusion similarity of the old and new asphalt by weighted average. The weighted formula is:

[0137] ,

[0138] Among them, is the total number of layers, is the weight of the -th layer.

[0139] Specifically, this step uses the DTW algorithm to calculate the minimum regularization distance of each layer of film, and defines the fusion similarity index with an exponential function to quantitatively describe the chemical composition similarity of the old and new asphalt.

[0140] Step S4. On the basis of the step S1 of layered extraction of samples, use the microscopic infrared spectroscopy technology to scan the spectral distribution of each layer of asphalt film on the surface of the RAP material particles, and capture the spectral characteristic changes in the local area; combine the FSI results calculated in step S3 to perform regional analysis on the spatial distribution of the particle surface and generate a fusion heat map;

[0141] The steps for performing regional analysis on the spatial distribution of the particle surface are,

[0142] Perform a grid scan and divide the surface of the RAP particles into two-dimensional grids, and the position of each grid point is , where , represents the row and column positions of the grid,

[0143] At each grid point collect the spectrum , and extract the characteristic peaks and the corresponding absorbance intensity , and the extraction content is expressed as:

[0144] ,

[0145] where, represents the spectral signal of the grid point , is the number of characteristic peaks on the grid point , is the Dirac function, used to mark the position of the wave number .

[0146] The steps to generate the fusion heat map are as follows:

[0147] Perform regional feature calculation, and combine the calculated in step S3 to calculate the regional feature value for the grid point, and the calculation formula is:

[0148] ,

[0149] where, represents the regional feature value of the grid point , is the total number of layers, is the fusion similarity of the th layer, is the two-dimensional Gaussian kernel function, used to weight the influence of adjacent points,

[0150] After normalization, generate the fusion heat map :

[0151] ,

[0152] where, is the heat map value after normalization, and are respectively 's minimum and maximum values.

[0153] Specifically, by combining microscopic infrared spectroscopy with FSI analysis, the spectral distribution on the particle surface is regionally characterized, and the generated fusion heat map visually displays the distribution characteristics of the new and old asphalt, forming basic evaluation data.

[0154] Step S5: Combine the FSI results calculated in step S3 with the fusion heat map generated in step S4 to analyze the overall fusion uniformity characteristics of the new and old asphalt, and construct an overall fusion uniformity evaluation UFM model; the UFM model quantifies the fusion depth and uniformity of the new and old asphalt by integrating local fusion characteristics and spectral similarity data, and generates an intuitive visualization result, providing data support and theoretical basis for optimizing the regeneration process and construction parameters;

[0155] The steps for constructing the overall fusion uniformity evaluation UFM model are as follows:

[0156] Calculate the local uniformity, and define the local uniformity index as :

[0157] ,

[0158] where is the local uniformity value of the grid point , is the gradient amplitude of the heat map at the point , indicating the degree of local change,

[0159] Calculate the global uniformity, and calculate the global uniformity average value based on the local uniformity , and the calculation formula is:

[0160] ,

[0161] where represents the average uniformity value of all grid points, and are the number of grid divisions,

[0162] Calculate the standard deviation of the local uniformity , and the calculation formula is:

[0163] ,

[0164] where represents the degree of uniformity fluctuation.

[0165] The steps for constructing the overall fusion uniformity evaluation UFM model also include

[0166] Construct the UFM model, based on the uniformity average value and the standard deviation Construct an overall fusion uniformity evaluation model , the model is expressed as:

[0167] ,

[0168] Among them, represents the overall fusion uniformity index,

[0169] Perform regional fluctuation analysis, and calculate the uniformity fluctuation index based on the local second-order gradient of the heat map , and the calculation formula is:

[0170] ,

[0171] Among them, represents the spatial fluctuation intensity of the heat map, is the Laplacian operator of the heat map, which measures the degree of local change intensity.

[0172] Specifically, by defining local uniformity, global uniformity, and fluctuation characteristics, construct the UFM model, quantify the fusion state of new and old asphalt from multiple dimensions, and integrate local changes and global characteristics to provide comprehensive and reliable quantification for practical applications.

[0173] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. A method for quantifying the degree of fusion of new and old asphalt, characterized by: include, Step S1, using a selective solvent to extract the asphalt film on the surface of the RAP material in layers, obtaining asphalt film samples at different layers, dissolving the extracted asphalt film samples at each layer and forming a uniform film by potassium bromide flake technology; Step S2, using a Fourier transform infrared (FTIR) spectrometer to perform spectral analysis on the thin film samples of each layer formed in step S1, to obtain spectral characteristic data and characteristic peaks, to pre-process the spectral characteristic data, including baseline correction and standardization, and to convert the characteristic peaks and spectral characteristic data into a standardized curve; Step S3, inputting the standardized curves of each layer of asphalt film obtained in step S2 into the dynamic time warping DTW algorithm, calculating the minimum warping distance between the new and old asphalt, and defining the fusion similarity index FSI based on the distance; Step S4, based on the layered extraction samples in step S1, the spectral distribution of each layer of asphalt film on the surface of RAP material particles is scanned by using micro-infrared spectroscopy technology to capture the changes in spectral characteristics of local areas; combined with the FSI results calculated in step S3, the spatial distribution of the particle surface is regionalized and analyzed to generate a fusion heat map; Step S5, combining the FSI result calculated in step S3 with the fusion heat map generated in step S4, analyzing the overall fusion uniformity characteristics of the new and old asphalt, and constructing a UFM model for evaluating the overall fusion uniformity.

2. A method for quantifying the degree of fusion of new and old asphalt as claimed in claim 1, characterized in that: In step S1, sample preparation and layered extraction are performed, and the sample preparation step includes: Place the RAP material on a sieve to remove large particles and debris, rinse with anhydrous ethanol or deionized water to remove surface dust and impurities, and then dry. According to the polarity of the asphalt component of the target extraction layer, a solvent system with different polarity gradients is selected for dissolution, and the solvent polarity ratio is adjusted according to the stratification target. The solvent ratio adjusted according to the stratification target is set as follows: First extraction: Use low polarity solvent to dissolve non-polar components. Second extraction: Use medium polarity solvent to extract the gum. The third extraction layer: using a highly polar solvent to dissolve the asphaltenes; The steps of the layered extraction are: The RAP material is placed in a beaker, and a low-polarity solvent is added to mix with the RAP and stirred to obtain a mixture; the mixture is then centrifuged in a centrifuge to separate the dissolved asphalt solution and the undissolved residual particles, and the undissolved particles are repeatedly extracted with a fresh first solvent to completely extract the target component; the residual particles are then transferred to a new beaker, and medium-polarity and high-polarity solvents are added in sequence, and the soaking and centrifugation steps are repeated to obtain asphalt solutions of different levels; The asphalt solution extracted from each layer was evaporated by a rotary evaporator to remove excess solvent, thus obtaining asphalt samples of different layers; Dissolve each layer of asphalt samples obtained by extraction in carbon tetrachloride or dichloromethane, stir thoroughly, drop the solution on the potassium bromide window slice, spread it evenly with a glass rod to evenly cover the solution; then place the slice in a drying oven and let it stand to dry to form a uniform film.

3. A method for quantifying the degree of fusion of new and old asphalt as claimed in claim 2, characterized in that: The steps of obtaining the spectral characteristic data and the characteristic peak value and preprocessing the spectral characteristic data are as follows: Scan the sample with an FTIR spectrometer and record the absorption spectrum over a range of wavenumbers , defined as: ， in, The wave number is The absorbance at The wave number is The background light intensity at The wave number is The sample transmission light intensity at The spectral data was baseline corrected to remove the background signal. The correction formula is: ， in, The wave number is The corrected absorbance is The wave number is The fitted baseline function at The corrected spectrum is standardized to eliminate the amplitude difference. The standardization formula is: ， in, The wave number is The standardized absorbance at and represent the minimum and maximum values ​​of the corrected spectrum, respectively.

4. A method for quantifying the degree of fusion of new and old asphalt as claimed in claim 3, characterized in that: The step of converting the characteristic peak value and spectral characteristic data into a standardized curve is: Characteristic peak extraction is performed, and the characteristic peak position and intensity are identified by the first-order derivative. The identification formula is: ， ， in, Indicates The characteristic peak wave number, Wave number The normalized absorbance intensity at A standardized curve is constructed based on the extracted characteristic peaks. The curve formula is: ， in, Indicates Normalized curve of the thin film sample, is the total number of characteristic peaks, and Respectively Layer of thin film The wave number and intensity of the characteristic peaks, is the Dirac function, label the wave number location.

5. A method for quantifying the degree of fusion of new and old asphalt as claimed in claim 4, characterized in that: The steps of calculating the minimum regular distance between the new and old asphalt and defining the fusion similarity index FSI based on the distance are as follows: Input the normalization curve, set The standardized curves of the new and old asphalt samples are and , define the matching path of the two curves , so that the total path distance is minimized, the path calculation formula is: ， in, is the total number of path points, and The first The wave number position of the point in the new and old curves, Calculate the total distance of the matching path using the following formula: ， in, For the The minimum regular distance between the new and old asphalt layers, For path The weight of the point, represents the Euclidean distance, defined as .

6. A method for quantifying the degree of fusion of new and old asphalt as claimed in claim 5, characterized in that: The step of calculating the minimum regularization distance between the new and old asphalt and defining the fusion similarity index FSI based on the distance also includes: Fusion similarity definition, based on Definition Layer fusion similarity index , the fusion formula is: ， in, is the distance adjustment factor, The overall fusion similarity of new and old asphalt is calculated by weighted average, and the weighted formula is: ， in, is the total number of layers, For the The weight of the layer.

7. A method for quantifying the degree of fusion of new and old asphalt as claimed in claim 6, characterized in that: The step of regionalizing the spatial distribution of the particle surface is: Perform grid scanning to divide the surface of RAP particles into The two-dimensional grid of each grid point is ,in , Indicates the row and column positions of the grid, At each grid point Collect spectra , and extract characteristic peaks and the corresponding absorbance intensity , the extracted content is expressed as: ， in, Represents a grid point The spectral signal, is the grid point The number of characteristic peaks on is the Dirac function, used to mark the wave number location.

8. A method for quantifying the degree of fusion of new and old asphalt as claimed in claim 7, characterized in that: The steps of generating the fusion heat map are: Perform regional characteristic calculations, combined with the calculations in step S3 , calculate the regional characteristic value for the grid point , the calculation formula is: ， in, Represents a grid point The regional characteristic value of is the total number of layers, For the The fusion similarity of the layers, is a two-dimensional Gaussian kernel function used to weight the influence of neighboring points. Generate fusion heat map after normalization : ， in, is the normalized heat map value, and They are The minimum and maximum values ​​of .

9. A method for quantifying the degree of fusion of new and old asphalt as claimed in claim 8, characterized in that: The steps of constructing the overall fusion uniformity evaluation UFM model are: Calculate the local uniformity and define the local uniformity index as : ， in, is the grid point The local uniformity value of For heatmap at point The gradient amplitude indicates the degree of local change. Calculate global uniformity based on local uniformity Calculate the global uniformity average , the calculation formula is: ， in, represents the average uniformity of all grid points, and is the number of grid divisions, Calculating local uniformity Standard Deviation , the calculation formula is: ， in, Indicates the degree of uniformity fluctuation.

10. A method for quantifying the degree of fusion of new and old asphalt as claimed in claim 9, characterized in that: The step of constructing the overall fusion uniformity evaluation UFM model also includes: Constructing UFM model based on uniformity average and standard deviation Constructing an overall fusion uniformity evaluation model , the model is expressed as: ， in, Represents the overall fusion uniformity index, Perform regional fluctuation analysis and calculate uniformity fluctuation index based on local second-order gradient of heat map , the calculation formula is: ， in, represents the intensity of spatial fluctuations in the heat map, It is the Laplacian operator of the heat map, which measures the severity of local changes.

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